class_docstr: A module to perform token level classification tasks for Bert pretraining.
class_docstr_tok: ["A","module","to","perform","token","level","classification","tasks","for","Bert","pretraining","."]
docstr: Returns definitions of module output ports.
docstr_tok: ["Returns","definitions","of","module","output","ports","."]
code: def output_types(self) -> Optional[Dict[str, NeuralType]]:
      """
      Returns definitions of module output ports.
      """
      if not self.log_softmax:
          return {"logits": NeuralType(("B", "T", "C"), LogitsType())}
      else:
          return {
              "log_probs": NeuralType(("B", "T", "C"), LogprobsType())
          }
  
file_path: NeMo/nemo/collections/nlp/modules/common/token_classifier.py
imports: from dataclasses import dataclass
  from typing import Dict, Optional
  from torch import nn
  from nemo.collections.common.parts import MultiLayerPerceptron
  from nemo.collections.nlp.modules.common.classifier import Classifier
  from nemo.core.classes import typecheck
  from nemo.core.neural_types import LogitsType, LogprobsType, NeuralType
label_desc: Use image node_id 1 for calling the BertPretrainingTokenClassifier obj's underlying member method code with example usage: obj.output_types() and returns: dict, dict